Structural Path Analysis and Multiplier Decomposition within a Social Accounting Matrix Framework

Defourny, Jacques; Thorbecke, Erik

doi:10.2307/2232220

Cited by 429 publications

(241 citation statements)

References 6 publications

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“…Due to its accounting consistency, comprehensiveness in recording data and flexibility, the SAM approach (fix price linear models) in the last three decades has been extensively used to analyse (inter alia) growth strategies in developing economies (Robinson, 1989), income distribution and redistribution (Roland-Holst & Sancho, 1992), the circular flow of income (Pyatt & Round, 1979;Defourny & Thorbecke, 1984;Robinson & Roland-Holst 1988), price formation (Roland-Holst & Sancho, 1995), structural and policy analysis of the agricultural sector in developed (Rocchi, 2009) and developing countries (Arndt et al, 2000), and the effects of public policy on poverty reduction (De Miguel-Velez & Perez-Mayo, 2010).…”

Section: Sams and Multipliersmentioning

confidence: 99%

Employing social accounting matrix multipliers to profile the bioeconomy in the EU member states: is there a structural pattern?

Philippidis

Sanjuán

Ferrari

et al. 2014

Span. j. agric. res.

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The concept of 'bioeconomy' is gathering momentum in European Union (EU) policy circles as a sustainable model of growth to reconcile continued wealth generation and employment with bio-based sustainable resource usage. Unfortunately, in the literature an economy-wide quantitative assessment covering the full diversity of this sector is lacking due to relatively poor data availability for disaggregated bio-based activities. This research represents a first step by employing social accounting matrices (SAMs) for each EU27 member encompassing a highly disaggregated treatment of traditional 'bio-based' agricultural and food activities, as well as additional identifiable bioeconomic activities from the national accounts data. Employing backward-linkage (BL), forward-linkage (FL) and employment multipliers, the aim is to profile and assess comparative structural patterns both across bioeconomic sectors and EU Member States. The results indicate six clusters of EU member countries with homogeneous bioeconomy structures. Within cluster statistical tests reveal a high tendency toward 'backward orientation' or demand driven wealth generation, whilst inter-cluster statistical comparisons by bio-based sector show only a moderate degree of heterogeneous BL wealth generation and, with the exception of only two sectors, a uniformly homogeneous degree of FL wealth generation. With the exception of forestry, fishing and wood activities, bio-based employment generation prospects are below non bioeconomy activities. Finally, milk and dairy are established as 'key sectors'.

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Section: Sams and Multipliersmentioning

confidence: 99%

Employing social accounting matrix multipliers to profile the bioeconomy in the EU member states: is there a structural pattern?

Philippidis

Sanjuán

Ferrari

et al. 2014

Span. j. agric. res.

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“…. We, therefore, had to come up with a second modification to the traditional LCA methodology, inspired by the structural path analysis (Defourny and Thorbecke 1984;Lenzen 2007) and the power series (PS) methods (Suh and Heijungs 2007). Both methods solve Eq.…”

Section: Temporally Differentiated Lci Calculation Methodsmentioning

confidence: 99%

The ESPA (Enhanced Structural Path Analysis) method: a solution to an implementation challenge for dynamic life cycle assessment studies

Beloin-Saint-Pierre

Heijungs

Blanc

2014

Int J Life Cycle Assess

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Purpose By analyzing the latest developments in the dynamic life cycle assessment (DLCA) methodology, we identify an implementation challenge with the management of new temporal information to describe each system we might want to model. To address this problem, we propose a new method to differentiate elementary and process flows on a temporal level, and explain how it can generate temporally differentiated life cycle inventories (LCI), which are necessary inputs for dynamic impact assessment methods. Methods First, an analysis of recent DLCA studies is used to identify the relevant temporal characteristics for an LCI. Then, we explain the implementation challenge of handling additional temporal information to describe processes in life cycle assessment (LCA) databases. Finally, a new format of temporal description is proposed to minimize the current implementation problem for DLCA studies. Results and discussion A new format of process-relative temporal distributions is proposed to obtain a temporal differentiation of LCA database information (elementary flows and product flows). A new LCI calculation method is also proposed since the new format for temporal description is not compatible with the traditional LCI calculation method. Description of the requirements and limits for this new method, named enhanced structural path analysis (ESPA), is also presented. To conclude the description of the ESPA method, we illustrate its use in a strategically chosen scenario. The use of the proposed ESPA method for this scenario reveals the need for the LCA community to reach an agreement on common temporal differentiation strategies for future DLCA studies. Conclusions We propose the ESPA method to obtain temporally differentiated LCIs, which should then require less implementation effort for the system-modeling step (LCA database definition), even if such concepts cannot be applied to every process.

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“…En consecuencia, la MCS contiene necesariamente más información que la MIP y, de acuerdo con el formato estándar convencional, cada cuenta tiene una fila que especifica sus ingresos (recursos) y una columna que especifica sus gastos (usos), dicho de otro modo, la MCS es una matriz cuadrada en donde el total por fila es exactamente igual al total por columna (ingreso=gasto) (Defourney and Thorbecke, 1984 El cuadro 3 hace patente que con la información de la MIP solamente la cuenta de las Actividades productivas está balanceada, todas las demás presentan desbalances más o menos grandes, debido a que la MIP no contiene la información necesaria que debe ser integrada en la MCS. Por ejemplo, en el caso de los…”

Section: Elaboración De La Macro Matrizunclassified

Matriz de contabilidad social y análisis de sectores productivos en México

Rodríguez

2017

CyA

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El presente artículo ha sido aceptado para su publicación en la revista Contaduría y Administración. Actualmente se encuentra en el proceso de revisión y corrección sintáctica, razón por la cual su versión final podría diferir sustancialmente de la presente. Una vez que el artículo se publica ya no aparecerá más en esta sección de artículos de próxima publicación, por lo que debe citarse de la siguiente manera:Núñez Rodríguez, G.

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Structural Path Analysis and Multiplier Decomposition within a Social Accounting Matrix Framework

Cited by 429 publications

References 6 publications

Employing social accounting matrix multipliers to profile the bioeconomy in the EU member states: is there a structural pattern?

Employing social accounting matrix multipliers to profile the bioeconomy in the EU member states: is there a structural pattern?

The ESPA (Enhanced Structural Path Analysis) method: a solution to an implementation challenge for dynamic life cycle assessment studies

Matriz de contabilidad social y análisis de sectores productivos en México

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